Nasrin Rastegarvand, H. Soleimanjahi, E. Arefian, M. Pourkarim
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Application of Bioinformatics Tools for the Prediction of Helper MicroRNAs for Improvement of Oncolytic Virus Efficacy
Purpose. Oncolytic Reoviruses, as a self-limiting virus, can be used in cancer treatment, because they have the ability to replicate in tumor cells selectively and destroy them. Studies show that some immune response proteins may interfere with the virus life cycle. So, the main aim of this bioinformatic study is to check which microRNA is able to target some reovirus inhibitory proteins. Experimental Design. By use of online bioinformatics software, the microRNAs that could target inhibitory genes were selected. Then, other features like content ++ score and cell type were checked and finally the eligible microRNAs were determined. Results. After choosing 15 inhibitory proteins, analysis was performed and finally 37 microRNAs which could target inhibitory proteins in colorectal cell lines were selected. In the end, by investigation of web-based tools, just two microRNAs were finalized. Conclusions and Clinical Relevance. This bioinformatic study shows that microRNA-140 and microRNA-92a have the potential to target some inhibitory proteins which interfere with oncolytic Reovirus replication and it may help in the optimal use of this virus as a cancer treatment. Because selective reproduction of Reovirus in tumor cells, as a nonchemical therapy, can be a good way to overcome this disease with broad advantages.
期刊介绍:
Cellular Microbiology aims to publish outstanding contributions to the understanding of interactions between microbes, prokaryotes and eukaryotes, and their host in the context of pathogenic or mutualistic relationships, including co-infections and microbiota. We welcome studies on single cells, animals and plants, and encourage the use of model hosts and organoid cultures. Submission on cell and molecular biological aspects of microbes, such as their intracellular organization or the establishment and maintenance of their architecture in relation to virulence and pathogenicity are also encouraged. Contributions must provide mechanistic insights supported by quantitative data obtained through imaging, cellular, biochemical, structural or genetic approaches.